this post was submitted on 01 Aug 2024
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LLMs: using statistics to generate reasonable-sounding wrong answers from bad data.
Often the answers are pretty good. But you never know if you got a good answer or a bad answer.
And the system doesn't know either.
For me this is the major issue. A human is capable of saying "I don't know". LLMs don't seem able to.
Accurate.
No matter what question you ask them, they have an answer. Even when you point out their answer was wrong, they just have a different answer. There's no concept of not knowing the answer, because they don't know anything in the first place.
The worst for me was a fairly simple programming question. The class it used didn't exist.
"You are correct, that class was removed in OLD version. Try this updated code instead."
Gave another made up class name.
Repeated with a newer version number.
It knows what answers smell like, and the same with excuses. Unfortunately there's no way of knowing whether it's actually bullshit until you take a whiff of it yourself.
So instead of Prompt Engineer, the more accurate term should be AI Taste Tester?
From what I’ve seen you’ll need an iron stomach.